Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec

Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec

Mereka bentuk rangkaian yang berkesan dan berprestasi tinggi memerlukan pencirian dan pemodela punca trafik rangkaian yang tepat. Tesis ini menyediakan satu kajian tentang penghantaran, pemodelan dan analisis video variable bit rate (VBR) yang merupakan asas reka bentuk protokol dan penggunaan rangk...

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Main Author: Ahmadpour, Sima
Format: Thesis
Language:English
Published: 2016
Subjects:
QA75.5-76.95 Electronic computers
Computer science
Online Access:http://eprints.usm.my/31806/1/SIMA_AHMADPOUR_24%28NN%29.pdf
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spelling my-usm-ep.318062019-04-12T05:25:25Z Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec 2016-02 Ahmadpour, Sima QA75.5-76.95 Electronic computers. Computer science Mereka bentuk rangkaian yang berkesan dan berprestasi tinggi memerlukan pencirian dan pemodela punca trafik rangkaian yang tepat. Tesis ini menyediakan satu kajian tentang penghantaran, pemodelan dan analisis video variable bit rate (VBR) yang merupakan asas reka bentuk protokol dan penggunaan rangkaian yang cekap dalam penghantaran video. Dengan ini, satu model trafik video VBR yang dikodkan oleh scalable video codec (SVC) telah dicadangkan. EDAR (1) dapat menjana siri video dengan tepat di mana siri ini bersifat seakan-akan trafik video yang sebenar. Model ini telah disahkan dengan menggunakan pelbagai statistik untuk membandingkan jejak simulasi da asal. Pengesahan ini telah dilakukan melalui pengukuran grafik (Quantile-Quantile plot) dan statistik (Kolmogorov-Smirnov, Jumlah Ralat Berganda (SSE), dan Kecekapan Relatif (RE)) serta pengesahan secara bersilang. Designing an effective and high performance network requires an accurate characterization and modelling of the network traffic. This work involves the analysis and modelling of the Variable Bit Rate (VBR) of video traffic, usually described as the core of the protocol design and efficient network utilization for video transmissions. In this context, an Enhanced Discrete Autoregressive (EDAR (1)) model for the VBR video traffic model, which is encoded by a Scalable Video Codec (SVC), has been proposed. The EDAR (1) model was able to accurately generate video sequences, which are very close to the actual video traffic in terms of accuracy. The model is validated using statistical tests in order to compare simulated and original traces. The validation is done using graphical (Quantile-Quantile plot) and statistical measurements (Kolmogorov-Smirnov, Sum of Squared Error, and Relative Efficiency), as well as cross-validation. 2016-02 Thesis http://eprints.usm.my/31806/ http://eprints.usm.my/31806/1/SIMA_AHMADPOUR_24%28NN%29.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer (School of Computer Sciences)
institution Universiti Sains Malaysia
collection USM Institutional Repository
language English
topic QA75.5-76.95 Electronic computers
Computer science
spellingShingle QA75.5-76.95 Electronic computers
Computer science
Ahmadpour, Sima
Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
description Mereka bentuk rangkaian yang berkesan dan berprestasi tinggi memerlukan pencirian dan pemodela punca trafik rangkaian yang tepat. Tesis ini menyediakan satu kajian tentang penghantaran, pemodelan dan analisis video variable bit rate (VBR) yang merupakan asas reka bentuk protokol dan penggunaan rangkaian yang cekap dalam penghantaran video. Dengan ini, satu model trafik video VBR yang dikodkan oleh scalable video codec (SVC) telah dicadangkan. EDAR (1) dapat menjana siri video dengan tepat di mana siri ini bersifat seakan-akan trafik video yang sebenar. Model ini telah disahkan dengan menggunakan pelbagai statistik untuk membandingkan jejak simulasi da asal. Pengesahan ini telah dilakukan melalui pengukuran grafik (Quantile-Quantile plot) dan statistik (Kolmogorov-Smirnov, Jumlah Ralat Berganda (SSE), dan Kecekapan Relatif (RE)) serta pengesahan secara bersilang. Designing an effective and high performance network requires an accurate characterization and modelling of the network traffic. This work involves the analysis and modelling of the Variable Bit Rate (VBR) of video traffic, usually described as the core of the protocol design and efficient network utilization for video transmissions. In this context, an Enhanced Discrete Autoregressive (EDAR (1)) model for the VBR video traffic model, which is encoded by a Scalable Video Codec (SVC), has been proposed. The EDAR (1) model was able to accurately generate video sequences, which are very close to the actual video traffic in terms of accuracy. The model is validated using statistical tests in order to compare simulated and original traces. The validation is done using graphical (Quantile-Quantile plot) and statistical measurements (Kolmogorov-Smirnov, Sum of Squared Error, and Relative Efficiency), as well as cross-validation.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ahmadpour, Sima
author_facet Ahmadpour, Sima
author_sort Ahmadpour, Sima
title Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
title_short Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
title_full Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
title_fullStr Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
title_full_unstemmed Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec
title_sort enhanced statistical modelling for variable bit rate video traffic generated from scalable video codec
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Sains Komputer (School of Computer Sciences)
publishDate 2016
url http://eprints.usm.my/31806/1/SIMA_AHMADPOUR_24%28NN%29.pdf
_version_ 1747820491913035776

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